How to Create a Voronoi Treemap in Tableau with Viz Extensions

Overview

A Voronoi treemap is a type of data visualization that combines the concepts of treemaps (which show hierarchical data) with Voronoi diagrams (which partition space based on proximity). Instead of using rectangular sections like a traditional treemap, a Voronoi treemap creates irregularly shaped cells that proportionally represent different data elements.

Example of Voronoi Treemap

Step-by-Step Guide

To create a Voronoi treemap in Tableau. Add the Voronoi treemap viz extension by going to the Marks card and select Add Extension.

On the pop-up window - go to the search bar and search “Voronoi”.

Select Voronoi treemap by LaDataViz and open it.

Notice the changes on the marks card and the view.

Note you can purchase the extension to enjoy its full features and capabilities.

In this example using the Sample – Superstore dataset, I am going to create a simple Voronoi diagram by dragging State to the color and detail shelf then add Sales to the size shelf.

This creates a Voronoi diagram allowing users to compare Sales proportions at a glance.

Note the area size in the Voronoi treemap is proportional to the Sales generated by the State.

Using the same technique, you can visualize hierarchical data (such as: Category >> Sub-Category) by.

• Dragging Category to the detail and color shelf.

• Next add Sub-Category to the detail shelf.

• And Sales to the size shelf.

This creates a Voronoi treemap as shown below.

Formatting Voronoi Treemap

There are several ways you can format your Voronoi treemap in Tableau using the Format Extension option.

Some of the formatting options available include.

• Changing the Shape Type of the viz.

• Choosing the appropriate color palette as well as displaying the legend on the viz.

• Customizing the labels.

• Customizing the background color as well as the width and height of the viz.

Here are some of the Shape Types you can use to represent your data.

Ellipse

Triangle

Rectangle

Square

Conclusion

Voronoi treemaps offer a visually engaging and intuitive way to represent hierarchical data, making complex relationships more accessible and interpretable. Their organic, irregular cell structures provide a refreshing alternative to traditional rectangular treemaps, improving readability while maintaining proportional data representation. This unique visualization technique finds applications in business analytics, scientific research, urban planning, and digital design, helping users uncover insights in an efficient and aesthetically pleasing manner. As data visualization continues to evolve, Voronoi treemaps stand out as a powerful tool for presenting intricate datasets with clarity and impact.

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